diff --git a/SourceDetection/LowSurfaceBrightness.ipynb b/SourceDetection/LowSurfaceBrightness.ipynb
index 50797916..672068ce 100644
--- a/SourceDetection/LowSurfaceBrightness.ipynb
+++ b/SourceDetection/LowSurfaceBrightness.ipynb
@@ -7,10 +7,10 @@
     "# Low-Surface Brightness Source Detection\n",
     "\n",
     "<br>Owner: **Alex Drlica-Wagner** ([@kadrlica](https://github.com/LSSTScienceCollaborations/StackClub/issues/new?body=@kadrlica))\n",
-    "<br>Last Verified to Run: **2018-07-22**\n",
-    "<br>Verified Stack Release: **w201829**\n",
+    "<br>Last Verified to Run: **2018-08-13**\n",
+    "<br>Verified Stack Release: **v16.0**\n",
     "\n",
-    "This Notebook demonstrates how to run the source detection, measurment, and deblending algorithms with a focus on optimizing for low-surface brightness object detection. It attempts to split out the source detection and measurement algorithms from `processCCD` and apply them to the search for low surface brightness galaxies. The content of this notebook builds off of Robert Lupton's [Greco LSB.ipynb](https://github.com/RobertLuptonTheGood/notebooks/blob/master/Demos/Greco%20LSB.ipynb) with some source detection and measurement details from [Tune Detection.ipynb](https://github.com/RobertLuptonTheGood/notebooks/blob/master/Demos/Tune%20Detection.ipynb) and [Kron.ipynb](https://github.com/RobertLuptonTheGood/notebooks/blob/master/Demos/Kron.ipynb).\n",
+    "This Notebook demonstrates how to run the source detection, measurment, and deblending algorithms with a focus on optimizing for low-surface brightness object detection. It attempts to split out the source detection and measurement algorithms from `processCCD` and apply them to the search for low surface brightness galaxies. The content of this notebook builds off of an analysis from Johnny Greco, adapted into notebook form in Robert Lupton's [Greco LSB.ipynb](https://github.com/RobertLuptonTheGood/notebooks/blob/master/Demos/Greco%20LSB.ipynb). Some source detection and measurement details come from [Tune Detection.ipynb](https://github.com/RobertLuptonTheGood/notebooks/blob/master/Demos/Tune%20Detection.ipynb) and [Kron.ipynb](https://github.com/RobertLuptonTheGood/notebooks/blob/master/Demos/Kron.ipynb).\n",
     "Interaction with `lsst.afw.display` was also improved by studying Michael Wood-Vasey's [DC2_Postage Stamps.ipynb](https://github.com/LSSTDESC/DC2_Repo/blob/master/Notebooks/DC2_Postage_Stamps.ipynb).\n",
     "\n",
     "### Learning Objectives:\n",
@@ -111,7 +111,7 @@
    "source": [
     "### Data access\n",
     "\n",
-    "Here we use the `butler` to access a `calexp` from the Twinkles data subset. More information on the `butler` can be found in [Butler_Tutorial.ipynb](), while a deeper examination of the `calexp` object can be found in [Calexp_Tutorial.ipynb](). We expect the user to have a working knowledge of these objects."
+    "Here we use the `butler` to access a `calexp` from the Twinkles data subset. More information on the `butler` will be available in `Butler_Tutorial.ipynb` (TBD), while a deeper examination of the `calexp` object can be found in [Calexp_guided_tour.ipynb](https://github.com/LSSTScienceCollaborations/StackClub/blob/master/Basics/Calexp_guided_tour.ipynb). We expect the user to have a working knowledge of these objects."
    ]
   },
   {
@@ -449,7 +449,7 @@
    "source": [
     "if False:\n",
     "    sources.writeFits(\"outputTable.fits\")\n",
-    "    exposure.writeFits(\"example1-out.fits\")"
+    "    calexp.writeFits(\"example1-out.fits\")"
    ]
   },
   {
@@ -629,6 +629,13 @@
     "plt.gca().axis('off')"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "The procedure above masks all `DETECTED` pixels with a simplistic selection. However, the Stack provides an alternative mechanism for more directed masking through the [meas.base.noiseReplacer](http://doxygen.lsst.codes/stack/doxygen/x_masterDoxyDoc/classlsst_1_1meas_1_1base_1_1noise_replacer_1_1_noise_replacer.html). The `noiseReplacer` takes as input the calexp object and the footprint set (`fpset`) returned `sourceDetectionTask`. With the `noiseReplacer`, it is possible to selectively replace a subset of the sources."
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {},